Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented ahead to the drilling process commences in the future operations.
Acrylic polymer/cement nanocomposites in dark and light colors have been developed for coating floors and swimming pools. This work aims to emphasize the effect of cement filling on the mechanical parameters, thermal stability, and wettability of acrylic polymer. The preparation was carried out using the casting method from acrylic polymer coating solution, which was added to cement nanoparticles (65 nm) with weight concentrations of (0, 1, 2, 4, and 8 wt%) to achieve high-quality specifications and good adhesion. Maximum impact strength and Hardness shore A were observed at cement ratios of 2 wt% and 4 wt%, respectively. Changing the filling ratio has a significant effect on the strain of the nanocomposites. The contact angle was i
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreThis paper describes the geotechnical properties of Al-Ammarah soil of Ammarah city in Messan Governorate-southern parts of Iraq. Data and other information taken from numbers of geotechnical reports that performed under the supervision of Consulting Engineering Bureau of Baghdad University. This research is devoted to study the correlation between different physical properties such as (LL, PI, LI, n,t, e) with different mechanical properties such as (qu, cc, cs, SPT). The correlation is verified using simple regression analysis. From the regression results it was found that there is direct correlation between different parameters. By using the correlation-with some information- preliminary investigation stages and studies of any s
... Show MoreThis paper describes the geotechnical properties of Al-Ammarah soil of Ammarah city in Messan Governorate-southern parts of Iraq. Data and other information taken from numbers of geotechnical reports that performed under the supervision of Consulting Engineering Bureau of Baghdad University. This research is devoted to study the correlation between different physical properties such as (LL, PI, LI, n,t, e) with different mechanical properties such as (qu, cc, cs, SPT). The correlation is verified using simple regression analysis. From the regression results it was found that there is direct correlation between different parameters. By using the correlation-with some information- preliminary investigation stages and studies of any s
... Show MoreObjectives Bromelain is a potent proteolytic enzyme that has a unique functionality makes it valuable for various therapeutic purposes. This study aimed to develop three novel formulations based on bromelain to be used as chemomechanical caries removal agents. Methods The novel agents were prepared using different concentrations of bromelain (10–40 wt. %), with and without 0.1–0.3 wt. % chloramine T or 0.5–1.5 wt. % chlorhexidine (CHX). Based on the enzymatic activity test, three formulations were selected; 30 % bromelain (F1), 30 % bromelain-0.1 % chloramine (F2) and 30 % bromelain-1.5 % CHX (F3). The assessments included molecular docking, Fourier-transform infrared spectroscopy (FTIR), viscosity and pH measurements. The efficiency
... Show MoreThe convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreCredential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi
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